The Spatial Mechanism and Predication of Rural Tourism Development in China: A Random Forest Regression Analysis

Abstract

Rural tourism has long been recognized as a significant strategy for promoting rural revitalization in China. Excessive development has had a number of negative consequences for rural tourism. As a result, there is a growing need to optimize the developmental framework of rural tourism in order to ensure its sustainable growth. This study focuses on key tourism villages and employs geostatistical analysis and the random forest methodology to elucidate the spatial mechanisms underlying rural tourism and identify potential areas for its development in China. The research findings reveal several important insights: (1) Key tourism villages exhibit a concentrated spatial distribution, characterized by pronounced regional disparities. (2) The intrinsic characteristics of rural areas and the conditions conducive to tourism development play pivotal roles in shaping rural tourism. Notably, cultural resources, tourism resources, rural accessibility, and tourism potential are identified as the primary influential factors. (3) Predictive modeling using random forest analysis indicates that densely populated areas in the eastern region retain the highest level of suitability for rural tourism. In contrast, the development of rural tourism in western and border regions encounters certain constraints. Additionally, the northern region encompasses larger expanses with high suitability, whereas the southern region is generally moderate. This comprehensive nationwide investigation provides valuable insights into the key aspects of rural tourism development and offers practical guidance for achieving sustainable rural tourism practices in China.